Googling in anatomy education: Can google trends inform educators of national online search patterns of anatomical syllabi?

2016 ◽  
Vol 10 (2) ◽  
pp. 152-159 ◽  
Author(s):  
Nigel Phelan ◽  
Shane Davy ◽  
Gerard W. O'Keeffe ◽  
Denis S. Barry
Keyword(s):  
Google Trends ◽  
Anatomy Education ◽  
Online Search ◽  
Search Patterns

scholarly journals Predictability analysis of the Pound’s Brexit exchange rates based on Google Trends data

2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Amaryllis Mavragani ◽  
Konstantinos Gkillas ◽  
Konstantinos P. Tsagarakis
Keyword(s):  
Exchange Rates ◽  
Human Behavior ◽  
Google Trends ◽  
Economic Variable ◽  
Traffic Data ◽  
Online Search ◽  
Research Areas ◽  
Search Patterns ◽  
Predictability Analysis ◽  
Directional Predictability

Abstract During the last decade, the use of online search traffic data is becoming popular in examining, analyzing, and predicting human behavior, with Google Trends being a popular tool in monitoring and analyzing the users' online search patterns in several research areas, like health, medicine, politics, economics, and finance. Towards the direction of exploring the Sterling Pound’s predictability, we employ Google Trends data from the last 5 years (March 1st, 2015 to February 29th, 2020) and perform predictability analysis on the Pound’s exchange rates to Euro and Dollar. The period selected includes the 2016 UK referendum as well as the actual Brexit day (January 31st, 2020), with the analysis aiming at analyzing the Pound’s relationships with Google query data on Pound-related keywords and topics. A quantile dependence method is employed, i.e., cross-quantilograms, to test for directional predictability from Google Trends data to the Pound’s exchange rates for lags from zero to 30 (in weeks). The results indicate that statistically significant quantile dependencies exist between Google query data and the Pound’s exchange rates, which point to the direction of one of the main implications in this field, that is to examine whether the movements in one economic variable can cause reactions in other economic variables.

scholarly journals Google search behavior for meningitis and its vaccines: an infodemiological study

BMC Neurology ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
John Angelo Luigi S. Perez ◽  
Adrian I. Espiritu ◽  
Roland Dominic G. Jamora
Keyword(s):  
Influenza Vaccine ◽  
Pneumococcal Vaccine ◽  
Rank Correlation ◽  
Infectious Agents ◽  
Online Behavior ◽  
Online Search ◽  
Search Volume ◽  
Search Patterns ◽  
Google Search ◽  
The Relationship

Abstract Background The internet has made significant contributions towards health education. Analyzing the pattern of online behavior regarding meningitis and vaccinations may be worthwhile. It is hypothesized that the online search patterns in meningitis are correlated with its number of cases and the search patterns of its related vaccines. Methods This was an infodemiological study that determined the relationship among online search interest in meningitis, its worldwide number of cases and its associated vaccines. Using Google Trends™ Search Volume Indices (SVIs), we evaluated the search queries “meningitis,” “pneumococcal vaccine,” “BCG vaccine,” “meningococcal vaccine” and “influenza vaccine” in January 2021, covering January 2008 to December 2020. Spearman rank correlation was used to determine correlations between these queries. Results The worldwide search interest in meningitis from 2008 to 2020 showed an average SVI of 46 ± 8.8. The most searched topics were symptoms, vaccines, and infectious agents with SVIs of 100, 52, and 39, respectively. The top three countries with the highest search interest were Ghana, Kazakhstan, and Kenya. There were weak, but statistically significant correlations between meningitis and the BCG (ρ = 0.369, p < 0.001) and meningococcal (ρ = 0.183, p < 0.05) vaccines. There were no statistically significant associations between the number of cases, influenza vaccine, and pneumococcal vaccine. Conclusion The relationships among the Google SVIs for meningitis and its related vaccines and number of cases data were inconsistent and remained unclear. Future infodemiological studies may expand their scopes to social media, semantics, and big data for more robust conclusions.

scholarly journals Analyzing online search patterns of music festival tourists

2020 ◽  
pp. 135481662094544
Author(s):  
Juan D Montoro-Pons ◽  
Manuel Cuadrado-García
Keyword(s):  
Graph Model ◽  
Online Search ◽  
Music Festivals ◽  
Random Graph Model ◽  
Music Festival ◽  
Exponential Random Graph ◽  
Search Patterns ◽  
Patterns Of Behavior ◽  
Online Search Behavior ◽  
Tourism Flows

Music festivals, as cultural events that induce tourism flows, intermediate both the cultural and travel experience. The present study analyzes online search behavior of potential attenders to a music festival. We hypothesize that the search process reveals latent patterns of behavior of cultural tourists planning to attend music festivals. To this end, information from Google Trends on queries related to three popular music festivals is used to build a network of search topics. Based on it, alternative exponential random graph model specifications are estimated. Findings support the general result of mediated information flows: music festivals induce planning and traveling queries. However, differences relating to the specificities of the cultural event are also found, in particular those regarding what nodes or queries supply the network with more useful information.

Understanding internet health search patterns: An early exploration into the usefulness of Google Trends

2008 ◽  
Vol 1 (4) ◽  
pp. 441-456 ◽  
Author(s):  
Peter J. Ellery ◽  
William Vaughn ◽  
Jane Ellery ◽  
Jennifer Bott ◽  
Kristin Ritchey ◽  
...  
Keyword(s):  
Google Trends ◽  
Search Patterns ◽  
Early Exploration

scholarly journals Distinct Diurnal and Day of Week Online Search Patterns Related to Common Eye Conditions

2020 ◽  
Author(s):  
Michael S. Deiner ◽  
Stephen D. McLeod ◽  
Julie M. Schallhorn ◽  
James Chodosh ◽  
Daniel H. Hwang ◽  
...  
Keyword(s):  
Search Engine ◽  
Time Of Day ◽  
Online Search ◽  
Eye Care ◽  
Cyclic Patterns ◽  
Diurnal Patterns ◽  
Search Terms ◽  
Eye Health ◽  
Search Patterns ◽  
Search Data

AbstractImportanceStudies suggest diurnal patterns of some eye conditions. Leveraging new information sources such as online search data to learn more about such patterns could improve understanding of patient eye-related conditions and well-being and improve timing of clinical and remote eye care.ObjectiveTo investigate our hypothesis that the public is likely to consistently search about different eye conditions at different hours of the day or days of week, we conducted an observational study using search data for terms related to eye conditions such as conjunctivitis. We asked if search volumes reflected diurnal or day-of-week patterns and if those patterns were distinct from each other.DesignHourly search data for eye-related and control search terms for 2018 were analyzed and compared.SettingData from 10 USA states.ExposureInternet search.ParticipantsPopulations that searched Google’s search engine using our chosen study terms.Main Outcome MeasuresCyclical hourly and weekly online search patterns.ResultsDistinct diurnal (p<0.001 for all search terms) and day-of-week search patterns for eye-related terms were observed but with differing peak time periods and cyclic strengths. Some diurnal patterns represented reported clinical patterns. Of the eye related terms, “conjunctivitis” and “pink eye” had the strongest diurnal cyclic patterns based on peak-to-trough ratios. Stronger signal was restricted to and peaked in mornings, and amplitude was higher on weekdays. In contrast, “dry eyes” had a higher amplitude diurnal pattern on weekends, with stronger signal occurring over a broader evening to morning period and peaking in early morning.Conclusions and RelevanceThe frequency of online searches for various eye conditions can show cyclic patterns according to time of day or week. Further studies to understand the reasons for these variations may help supplement current clinical understanding of eye symptom presentation and improve the timeliness of patient messaging and care interventions.Key PointsQuestionDo online public search engine queries for different eye-health terms follow hourly or daily patterns and do the patterns differ from each other or reflect what is known clinically?FindingsUnique hourly and day of week eye health related search patterns appear diurnal and can reflect what has been observed clinically.MeaningOnline search data may reflect timing of eye conditions and could improve clinical understanding of eye-related symptom occurrence, including outside of clinics. Knowing precisely when patient’s eye condition interests increase holds promise -for example to optimize timing and availability of local or remote eye care resources.

scholarly journals Comparing public interest on stone disease between developed and underdeveloped nations: are search patterns on google trends similar?

2021 ◽  
Vol 47 (5) ◽  
pp. 989-996
Author(s):  
Giovanni S. Marchini ◽  
Kauy V. M. Faria ◽  
Felippe L. Neto ◽  
Fábio César Miranda Torricelli ◽  
Alexandre Danilovic ◽  
...  
Keyword(s):  
Public Interest ◽  
Stone Disease ◽  
Google Trends ◽  
Search Patterns

scholarly journals COVID-19 Symptom-Related Google Searches and Local COVID-19 Incidence in Spain: Correlational Study (Preprint)

2020 ◽  
Author(s):  
Alberto Jimenez Jimenez ◽  
Rosa M Estevez-Reboredo ◽  
Miguel A Santed ◽  
Victoria Ramos
Keyword(s):  
Real Time ◽  
Influenza A ◽  
Time Lag ◽  
Population Level ◽  
H1n1 Influenza ◽  
Google Trends ◽  
Small Contribution ◽  
Search Patterns ◽  
Search Data ◽  
Google Search

BACKGROUND COVID-19 is one of the biggest pandemics in human history, along with other disease pandemics, such as the H1N1 influenza A, bubonic plague, and smallpox pandemics. This study is a small contribution that tries to find contrasted formulas to alleviate global suffering and guarantee a more manageable future. OBJECTIVE In this study, a statistical approach was proposed to study the correlation between the incidence of COVID-19 in Spain and search data provided by Google Trends. METHODS We assessed the linear correlation between Google Trends search data and the data provided by the National Center of Epidemiology in Spain—which is dependent on the Instituto de Salud Carlos III—regarding the number of COVID-19 cases reported with a certain time lag. These data enabled the identification of anticipatory patterns. RESULTS In response to the ongoing outbreak, our results demonstrate that by using our correlation test, the evolution of the COVID-19 pandemic can be predicted in Spain up to 11 days in advance. CONCLUSIONS During the epidemic, Google Trends offers the possibility to preempt health care decisions in real time by tracking people's concerns through their search patterns. This can be of great help given the critical, if not dramatic need for complementary monitoring approaches that work on a population level and inform public health decisions in real time. This study of Google search patterns, which was motivated by the fears of individuals in the face of a pandemic, can be useful in anticipating the development of the pandemic.

Distinct Diurnal and Day of Week Online Search Patterns Related to Common Eye Conditions (Preprint)

2021 ◽  
Author(s):  
Michael S Deiner ◽  
Stephen D. McLeod ◽  
Julie M. Schallhorn ◽  
James Chodosh ◽  
Daniel H. Hwang ◽  
...  
Keyword(s):  
Well Being ◽  
Early Morning ◽  
Time Of Day ◽  
Peak Time ◽  
Health Campaigns ◽  
Online Search ◽  
Diurnal Patterns ◽  
Search Terms ◽  
Search Patterns ◽  
Search Data

BACKGROUND Studies suggest diurnal patterns of occurrence of some eye conditions. Leveraging new information sources such as online search data to learn more about such patterns could improve understanding of patient eye-related conditions and well-being, and improve timing of clinical and remote eye care or of targeted online public health campaigns for hard-to-reach populations. OBJECTIVE To investigate our hypothesis that the public is likely to consistently search about different eye conditions at different hours of the day or days of week, we conducted an observational study using search data for terms related to eye conditions such as conjunctivitis. We assessed whether search volumes reflected diurnal or day-of-week patterns and if those patterns were distinct from each other. METHODS Design: Hourly search data for eye-related and control search terms for 2018 were analyzed and compared. Setting: Data from 10 USA states. Exposure: Internet search. Participants: Populations that searched Google’s search engine using our chosen study terms. Main Outcome Measures: Cyclical hourly and weekly online search patterns. RESULTS Distinct diurnal (P < .001 for all search terms) and day-of-week search patterns for eye-related terms were observed but with differing peak time periods and cyclic strengths. Some diurnal patterns represented those reported from prior clinical studies. Of the eye related terms, “pink eye” showed the largest diurnal amplitude-to-mean ratios. Stronger signal was restricted to and peaked in mornings, and amplitude was higher on weekdays. In contrast, “dry eyes” had a higher amplitude diurnal pattern on weekends, with stronger signal occurring over a broader evening to morning period and peaking in early morning. CONCLUSIONS The frequency of online searches for various eye conditions can show cyclic patterns according to time of day or week. Further studies to understand the reasons for these variations may help supplement current clinical understanding of eye symptom presentation and improve the timeliness of patient messaging and care interventions.

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